Korea Stock MCP demonstrates strong fundamentals with clear action-verb naming (get_*, search_*), well-structured descriptions for most tools (150-250 chars, balancing specificity with brevity), and comprehensive input schemas with proper types and parameter descriptions. Tool annotations (readOnlyHint, idempotentHint, destructiveHint) are correctly applied to the ping tool. However, output schemas are not explicitly documented in the tool definitions themselves, the descriptions mention what is returned (e.g., 'ticker, name, market and sector' for search_company) but formal schema documentation is absent. Risk handling is exceptional: ratio computation logic explicitly prevents fabricated values via null-safe functions (src/app/analysis/ratios.py), and the get_risk_flags tool documents that unavailable checks are listed separately. The codebase shows mature error handling philosophy (mask_error_details=True, ToolError/DartError passed through). Naming could be slightly more specific, search_company does not distinguish between ticker-code search vs. name search, though the description clarifies this. No security issues detected in tool parameters (no credentials exposed). Per-tool analysis reveals strong consistency across the 6 tools: all follow READ_ONLY pattern, all have verb-noun names, all include meaningful parameters with type and description constraints.

• Add explicit JSON Schema definitions for all tool return types. Example: { 'type': 'object', 'properties': { 'ticker': { 'type': 'string' }, 'name': { 'type': 'string' }, 'market': { 'enum': ['KOSPI', 'KOSDAQ'] }, 'sector': { 'type': 'string' } }, 'required': ['ticker', 'name'] }
• Add pagination to search_company: introduce 'limit' (1 - 50, default 20) and 'offset' parameters, and return 'total_count' in response to enable multi-page discovery.
• Encode range constraints in JSON Schema: for get_financials, add 'minimum': 2 and 'maximum': 10 to the 'years' property. For get_risk_flags, add 'minimum': 7 and 'maximum': 365 to 'disclosure_days'. Remove or augment the prose descriptions with these machine-readable constraints.
• For search_company 'query' parameter, add a pattern constraint (e.g., '^[0-9]{6}$|^[가-힣a-zA-Z0-9\s]+$') to document ticker vs. name format, or split into two separate parameters (ticker_code and company_name) to force explicit LLM intent.
• Add a 'field_names' parameter or separate tool to allow users to discover which financial fields are available in get_financials responses (e.g., revenue, operating_income, net_income, liabilities, equity, etc.) before committing to a full data call.
• Document error paths explicitly: e.g., 'If ticker is not found, returns {"error": "TICKER_NOT_FOUND", "message": "No listing found for ticker XXXXXX. Try search_company() first."}' so LLMs know to invoke search_company on failure.